Rice–wheat comparative genomics: Gains and gaps

Abstract

Rice and wheat provide nearly 40% of human calorie and protein requirements. They share a common ancestor and belong to the Poaceae (grass) family. Characterizing their genetic homology is crucial for developing new cultivars with enhanced traits. Several wheat genes and gene families have been characterized based on their rice orthologs. Rice–wheat orthology can identify genetic regions that regulate similar traits in both crops. Rice–wheat comparative genomics can identify candidate wheat genes in a genomic region identified by association or QTL mapping, deduce their putative functions and biochemical pathways, and develop molecular markers for marker-assisted breeding. A knowledge of gene homology facilitates the transfer between crops of genes or genomic regions associated with desirable traits by genetic engineering, gene editing, or wide crossing.

Headnote

ABSTRACT

Rice and wheat provide nearly 40% of human calorie and protein requirements. They share a common ancestor and belong to the Poaceae (grass) family. Characterizing their genetic homology is crucial for developing new cultivars with enhanced traits. Several wheat genes and gene families have been characterized based on their rice orthologs. Rice–wheat orthology can identify genetic regions that regulate similar traits in both crops. Rice–wheat comparative genomics can identify candidate wheat genes in a genomic region identified by association or QTL mapping, deduce their putative functions and biochemical pathways, and develop molecular markers for marker-assisted breeding. A knowledge of gene homology facilitates the transfer between crops of genes or genomic regions associated with desirable traits by genetic engineering, gene editing, or wide crossing.

Keywords:

Comparative genomics

Orthologs

Genes

Synteny

Genetic engineering

Molecular breeding

1. Introduction

Rice (Oryza sativa L.) and wheat (Triticum aestivum L.) are the most extensively cultivated and consumed cereals worldwide. Rice and wheat are cultivated on respectively 166.5 and 222 Mha for a total production of 513 and 779 Mt of grain in 2021–2022 [1]. Bread wheat, an allohexaploid (2n = 6x = 42) harboring the A, B, and D subgenomes, is a relatively new species that emerged approximately 8500–9000 years ago as a hybrid of T. turgidum (2n = 4x = 28, genome formula AABB) and Aegilops tauschii (2n = 2x = 14, DD). Triticum turgidum, a cultivated tetraploid species known for its threshability, was initially derived from two diploid species, T. urartu (2n = 2x = 14, AA) and Ae. speltoides (2n = 2x = 14, BB). The diploid parent A. tauschii is thus the D-genome donor to modern hexaploid wheat [2–5].

Cultivated rice (O. sativa) was domesticated from Asian wild rice (O. rufipogon) around 8000 years ago [6]. Researchers have generated genome sequences from diverse accessions of O. rufipogon and cultivated indica and japonica varieties to construct a map of rice genome variation [7]. Their findings suggested that cultivated rice originated from O. rufipogon but could not identify its domestication processes or geographic origins. A phylogeographic analysis [8] of O. rufipogon and O. sativa suggested that O. sativa indica was domesticated in a region south of the Himalaya mountain range, including eastern India, Myanmar, and Thailand, whereas O. sativa japonica was domesticated from wild rice in southern China. A survey [9] of the genetic diversity and population structure of 3010 Asian O. sativa accessions revealed 29 million single-nucleotide polymorphisms (SNPs), 2.4 million InDels, and 90,000 structural variations within and among populations.

Phylogenetic studies have revealed relationships among agricultural crops such as rice, wheat, and maize. Their family, the Poaceae, is one of the largest in the angiosperms, with around 11,000 species [10]. A whole-genome synteny-based phylogeny of angiosperms [11] suggested that the synteny tree could reshape our understanding of the evolution of these crops, as well as the origin of C4 lineages. Poaceae is a monophyletic group with two major subdivisions: the PACMAD clade, which includes the six subfamilies Panicoideae, Arundinoideae, Chloridoideae, Micrairoideae, Aristidoideae, and Danthonioideae [12], and the BEP (or BOP) clade, which includes Bambusoids, Oryzoids, and Pooids]. In contrast to the BEP clade, which uses the C3 photosynthesis pathway, the PACMAD lineage has evolved the C4 pathway [13]. However, the relationships between the PACMAD and BEP clades have rarely been described. In support of the phylogenetic relationships proposed by Zhao et al. [11], the International Wheat Genome Sequencing Consortium conducted a comparative phylogenomic survey [11] of gene family expansion and contraction in the wheat genome. It revealed a similar clustering pattern of species based on gene family profiles. The phylogenetic relationships among grass species in the BEP clade. These studies have provided insights into the evolutionary history of these important agricultural crops and have the potential to reshape our understanding of their relationships within the grass family. Further research is needed to confirm and refine these phylogenetic relationships and to explore their implications for crop improvement and evolutionary biology.

A limited number of genes have been cloned using map-based cloning techniques, despite the vast number of genes and/or QTL reported in wheat. Grass genomes, including those of wheat, barley, rice, millet, maize, and sorghum, exhibit large amounts of synteny and colinearity, according to various genomic comparisons [14–16]. Rice was the first to undergo genome sequencing [17]. Its chromosome number of 2n = 24 and smallest genome size (estimated at 400–430 Mb) among the major cereal crop genomes made sequencing economically feasible [18]. In contrast, wheat is a polyploid with a much larger genome size, close to 16,000 Mb [19], containing 2n = 6x chromosomes with three sets of related genomes (A, B, and D) and much duplicated and repeated DNA (25%–30% and over 80%, respectively). Though the genome complexity limits and slows study, this genome organization pattern in grass family members provides a powerful strategy for understanding the genetic makeup in terms of its structure and function and for finding genes in common wheat [20–23].

Rice–wheat homology-based cloning, which uses gene sequences of the model crop rice as references to find orthologous genes in wheat, has revealed many genes in common wheat. Ricewheat homology led to the discovery of the genes TaTGW6 [24,25], TaCwi-A1 [26], TaSus2-2A, TaSus1-7A, TaSus2-2B [4], TaGW2-6A, 6B [27–29], TaCKX6-D1 [30], TaSAP1-A1 [31], TaGS1a [32], TaGSD1 [33], and TaGASR-A [34]. Isolating and characterizing genes influencing common wheat's economic value will aid breeders in developing gene-based breeding plans to enhance yield and other traits of interest. Over 100 grain size-associated genes have been identified and functionally described in rice, but only about a fifth of them have been used as a template to study. This review discusses examples of wheat genes cloned and characterized using their rice orthologs as template genes. Not only individual wheat genes but some gene families have been characterized using their corresponding rice gene families as templates, among them the cytokinin [35] and COBRA-like [36] gene families. Several rice genes are proposed as potential templates to clone and characterize their wheat orthologs.

Studying rice and wheat homology sheds light on the evolution and organization of the genomes of these two cereal crops [37]. Comparative genomics studies have shown that rice and wheat share homologies in several genomic regions, indicating their common ancestry [38]. Mapping rice centromeric genes onto wheat aneuploid stocks allows identifying centromere homologies between wheat and rice chromosomes [37]. This can help in identifying chromosomal rearrangements and gene content and order that are not conserved as large chromosomal blocks as previously predicted [39]. Comparative sequence analysis of expressed sequence tags (ESTs) that were physically mapped in wheat chromosome bins to the public rice genome sequence using BLAST revealed numerous chromosomal rearrangements that will complicate the use of rice as a model for cross-species transfer of information in non-conserved regions [40]. Comparative analysis of protein–protein interactions in the defense response of rice and wheat has the potential to enhance the translation of advances in rice to wheat and other grasses [41]. Studying rice and wheat homology can shed light on the evolution and organization of their genomes and pangenomes, which can be useful in crop improvement strategies for increasing yield potential, stress tolerance, and input use efficiency of rice and wheat and their cropping systems [38–41].

2. Rice–wheat genome synteny

Over the past decade, the arrangement of cereal genomes, particularly those larger than the human genome, has been subjected to continued research. Wheat is one such example. It is a member of the Poaceae family, which underwent both grass-common tetraploidization (GCT) and a hybridization event between the wheat sub-genomes A, B, and D [20].

Several plant comparative genomic studies [42,43] have revealed similarity in both structure and function among grass genomes, despite their differences in genome size, chromosome number, and ploidy level. Comparative genomics is a way to find colinearity (identical gene order) and synteny (identical gene content) among genomes. Bioinformatics-based comparative genomics analyses, such as gene family and plant evolutionary studies, can be used to better comprehend genes or species evolution. Moreover, it broadens the understanding of the biological organization, evolutionary blueprint, divergence, conserved domains, gene structure, phylogenetic relationship, and orthologous and paralogous genes between two or more species by comparing genome structure and function [44]. This is made possible by the rapid advance of next-generation sequencing technologies, low sequencing costs, and the development of new bioinformatics software and tools in recent years.

In the beginning, a comparison of genomes was performed by reciprocal mapping of DNA probes [45]. Prior to the publication of the whole genome sequence of wheat, researchers focused on DNA markers mapped on individual chromosomes at low resolution (10 cM) for comparative genomics [46]. Considering rice and wheat, comparative genomics provides information on the genomic architecture of these two species, permitting searching for wheat orthologs in rice sequences or vice versa (Fig. 1). Visual comparison of the three subgenomes of bread wheat (A, B and D) and rice genome using SynVisio [47] also shows high long-range synteny between the three subgenomes and demonstrates a higher level of conservation of syntenic, colinear gene blocks than in the comparison with the rice genome (Fig. 2). The higher shared synteny helps to unveil the complex genomic relationships between wheat and rice, shedding light on their genetic evolution.

Comparative mapping followed by rice–wheat homology-based cloning has identified genes controlling similar characters. Grain weight is controlled by IAA-glucose hydrolase (TaTGW6) in both rice (OsTGW6) and wheat (TaTGW6) [27]. Several studies [40,46] have shown the conservation of orthologous sequences between rice and wheat using expressed sequence tags (ESTs). A Gene Ontology (GO) term analysis of conserved orthologous genes between rice and wheat shows preserved biological functions such as macromolecule biosynthesis and modification (19% of orthologs), regulation of gene expression (13% of orthologs), and nucleic acid metabolism (12% of orthologs) in both species (Fig. 2). The GO terms suggest that the highly conserved orthologous genes in rice and wheat are involved in fundamental biological processes such as growth, development, yield, genetic stability, and environmental adaptation. These conserved genes in crops represent a valuable genetic resource that can be used for marker-assisted selection, gene introgression, genetic modifications, trait stacking, gene editing, and crop modeling.

3. Grain yield

Yield is determined by three components: thousand-grain weight (TGW), grain number per spike (GNS), and total spike number per unit area (TSN per square meter), which are influenced by the genetic background of wheat [49]. A QTL controlling TGW, GNS, and spike number (SN per square meter) have been identified. The advent of high-throughput genotyping has accelerated the discovery of genetic loci associated with yield-component traits [50–52]. Jaiswal et al. [53] identified a novel SNP in the promoter sequence of TaGW2- 6A associated with grain weight in wheat. Similarly, in rice ortholog, a candidate gene D11 was associated with grain size (length and width) in an international collection of T. aestivum by GWAS [33]. Besides high-throughput genotyping, the comparative genomic approach of homology-based map cloning is gaining popularity in wheat because of its allopolyploidy and complex genome structure to isolate and discover genes [27,28,30] influencing grain yield. In this context, rice–wheat synteny came into the light when a gene sequence of rice was used as a reference to isolate and identify orthologous genes in wheat. The genes TaGw2, TaTGW6-A1, and TaTGW-7A linked to grain width and weight have been isolated and identified via rice–wheat homology-based cloning [27,28,54,55]. Cytokinin influences grain yield and its related traits [29]. Lu et al. [29] identified a novel allele named TaCKX6a02 that showed close association with grain size and weight in common wheat RILs developed from Jing 411 Hongmangchun 21. However, the identified homologous genes act as positive and negative regulators so that the sitespecific mutation can reverse the result of negative regulators in a positive direction. TaGW2-A1 is negatively associated with grain width and weight in hexaploid wheat. Still, a single-base substitution in a G-to-A transition in the splice acceptor site of exon 5 led to an increase instead of a decrease in TGW in tetraploid and hexaploid wheat [31]. Likewise, Zhai et al. [56] identified a novel allele of TaGW2-A1 that is responsible for increased grain weight but reduces grain number. Wheat genes and their rice orthologs associated with grain yield are listed in Table 1 and a proposed list of yield-associated rice genes as a potential template for cloning and characterizing their wheat orthologs is presented in Table 2.

4. Abiotic stresses

Plants, as sessile organisms, respond to stresses through various signaling pathways involving multiple genes and molecular and biochemical mechanisms. Among various abiotic stresses, heat and drought stress severely impair wheat growth, development, and productivity. It has been predicted [79,80] that every rise of 2 C will incur wheat yield losses of 42 Mt. Huizi et al. [81] stated that heat stress will reduce wheat production by 0.6% to 4.2% by 2071–2100 in the northern plains of China, which account for approximately 50% of China's wheat production [82]. Sometimes plants affected by high temperature stress also show symptoms of drought stress. Drought stress is a global issue. Drought is happening more frequently and for longer durations owing to global warming, which has increased the likelihood of yield losses [83]. Given that drought stress has reduced wheat production by up to 32% worldwide [84], it is essential to identify genes involved in response to heat and drought stress in wheat for climate-resilient breeding. Accordingly, this review discusses wheat–rice synteny in relation to heat and drought stress under separate headings.

4.1. Heat stress

Heat stress is one of the most important abiotic factors affecting wheat production worldwide. The temperature is expected to rise by 4.4 C by 2081–2100 if mitigation measures are not taken to minimize the impact of current human interventions towards the environment, greatly impacting wheat production and threatening global food security [85]. The severity of heat stress damage is determined by the duration of, and growth stage during, heat stress. Rice uses genetic technologies such as transcriptomics, qPCR, RNA-seq, mutagenesis, and transgenesis more than wheat [86]. These research trends are used to study orthologous genes in bread wheat (hexaploid species) with the largest genome size of 16 Gb. Wheat heat-responsive genes have been cloned and validated in Arabidopsis, tobacco, and rice [87–89]. Many functioning Arabidopsis and rice genes are used to locate orthologous wheat genes with similar biological functions. We have compiled in Table 1 heat-responsive genes in wheat that have been studied using rice genes as the basis for functional analysis.

4.2. Drought stress

Drought stress is another unavoidable consequence of global warming and climate change. It impairs crop performance by lowering photosynthesis, disrupting the source–sink relationship, and ultimately reducing grain yield. It also raises the concentration of reactive oxygen species (ROS) in the cell, inducing oxidative damage [94]. Multiple droughttolerance mechanisms at the gene/molecular level and QTL (including the WRKY, AP2/ERF, MYB, bZIP, NAC, DREB, and DRO gene families) have been discovered in both rice and wheat. Li et al. [95] established syntenic relationships between 56 TaSPL genes in wheat and their corresponding OsSPLs in rice and found TaSPL2, TaSPL6, TaSPL8, and TaSPL10 associated with abiotic stress. DRO1 orthologs in rice and wheat share 76% identity, implying a similar function in avoiding water deficit stress [96]. In addition, 83 orthologous genes have been reported between rice and wheat [97]. Despite the large number of orthologs shared by rice and wheat, not all have a functional relationship. A contrasting response to salt and drought stress was observed in OsCLR1-overexpressing rice lines [98]. Wheat genes and their rice orthologs responsive to drought stress are listed in Table 1 and a list of abiotic stress-responsive rice genes proposed as templates for cloning and characterization of their wheat orthologs is presented in Table 2.

5. Biotic stress

The adverse effect of unfavorable environmental factors on the morphology, physiology and molecular biology of the plant is called stress. When such environmental factors are living organisms, such as weeds, insects, pests, and pathogens, that alter the metabolic activities of an affected cell and ultimately the plant, it is called biotic stress. Biotic stress is a major source of pre- and postharvest losses in cereals, incurring losses of up to 35% [129,130]. Given that the genetic code of the plant stores the genetic basis for defense systems [131], characterizing disease or pest tolerance mechanisms, followed by discovering responsive genes and developing effective genetic markers and phenotypic selection indices, are essential for mitigating yield loss due to biotic stress. Rust is the most devastating disease of wheat globally. Black or stem rust (Puccinia graminis f. sp tritici), brown or leaf rust (P. triticina), and yellow or stripe rust (P. striiformis) are also reported [132] to have potential to infect rice. Though rice is a non-host of the rust pathogen, it still shows a non-host resistance reaction [133]. A wheat Lr34 gene ortholog has been identified in rice [134]. Lr34 confers durable resistance to the above rust causal organisms, as well as to powdery mildew (Blumeria graminis) in wheat, but the function of Lr34 is still unknown in rice [134]. The genomic sequence of the yellow rust resistance gene of wheat Yr17 is colinear with genomic regions on rice chromosome 4 and chromosome 7 [135]. Colinearity has also been well established among wheat chromosome 1B and rice chromosome 10 [40,136], and between wheat chromosome 3 and rice chromosome 1 [38,45,137,138]. Several biotic stress-resistance genes are present on these chromosomes, including those for glume blotch (Stagonospora nodorum) [139], stem rust (Puccinia graminis f. sp. tritici) [140], and leaf rust (P. recondita) resistance [141].

Over 20 rice blast-resistance genes have been discovered by rice genome sequencing and map-based cloning. Some newly discovered genes were later identified as alleles or orthologs of previously cloned genes [142–144]. The wheat TaWRKY68 gene is involved in growth and development and may act as a sharing signal component in wheat responses to various biotic stressors. TaWRKY68 may be a hub gene in wheat responses to biotic stresses. OsWRKY68 is a rice ortholog of TaWRKY68 [131]. Sometimes, owing to sequence conservation in molecular markers, no synteny block can be established between wheat and rice. In wheat stem sawfly resistance, synteny could not be established; however, a comparison between a Qss-3BL transcript of wheat and a protein sequence of rice showed a syntenic relationship with rice chromosome 1 [145].

Many genes that encode essential metabolic proteins (functional proteins) or regulatory proteins control complex response mechanisms [146]. Typical examples of such regulatory proteins are transcription factors and protein kinases [147–149]. The WRKY [131], NAC [150], and TIFY (previously known as Zinc finger protein expressed in Inflorescence Meristem) [151] TF families function in biotic and abiotic stress responses in plants. Syntenic analysis for these families between wheat and rice genome indicated the presence of orthologous genes and the presence of similar domains in both wheat and rice [131,151]. TaNAC8 shows similarity with rice OsNAC8 [150]. Wheat genes and their rice orthologs responsive to biotic stress are listed in Table 1 and a list of biotic stress-responsive rice genes proposed as templates for cloning and characterization of their wheat orthologs is presented in Table 2.

6. Micronutrients (iron and zinc)

Micronutrients are essential for plants and humans in small doses. Cereals naturally lack zinc (Zn) and iron (Fe), causing "hidden hunger" [174] in human populations. The two micronutrients share common pathways of uptake from the soil, root–shoot translocation, and loading into grain [175,176]. Plants have evolved and adopted two strategies to take up Fe from soil with limited Fe availability. Non-graminaceous plants such as Arabidopsis adopt strategy I, whereas graminaceous plants such as rice and wheat adopt strategy II (reducing and chelating) [177,178]. Several common orthologs involved in Fe acquisition of rice have been identified in the wheat A, B, and D subgenomes [179,180].

After acquisition via roots and transport in the plant or its parts (leaves, culms), the final parking place for Fe and Zn is the developing seed. Initially, plant roots release phytosiderophores, organic molecules with high iron affinity, into the rhizosphere to increase their solubility and availability. These phytosiderophores are derived from deoxymugineic acid (DMA) which is synthesized from S-adenosylmethionine (SAM) via several enzymatic reactions [181]. Wheat and rice possess several common enzymes involved in DMA synthesis. However, the pathway is initiated mainly from SAM, involved in Fe and Zn uptake or transport in plants [181]. The OsSAM2 ortholog of rice has been found in wheat [179]. Another enzyme, OsNas, converts SAM into nicotianamine (NA) in rice and has shown substantial sequence similarity with wheat genes [179–181]. Similarly, nicotianamine aminotransferase (NAAT) and deoxymugineic acid (DMAS) involved in NA aminotransferase and 20 -dioxygenase enzymes are orthologous to NAAT1 and DMAS1 genes [179]. Afterward, the phytosiderophores are released in the soil and then bind with Fe-IIl to form Fe-IIl - phytosiderophores complexes. Such complexes are absorbed by transporters such as yellow strip-like transporters (YSL). Rice yellow-stripe-like transporter genes OsYSL2, OsYSL3, OsYSL7, OsYSL8, OsYSL10, OsYSL11, OsYSL12, OsYSL13, OsYSL15, OsYSL16, and OsYSL18 are orthologous to corresponding wheat genes [179]. For Fe and Zn uptake, the wheat genome contains orthologs of genes involved in Methionine recycling (OsDEP, OsIDI4, OsMTN, OsMTK), Phenolics efflux transporter (OsPEZ2), NA efflux transporter (OsENA1), Phenolic compounds transporter (OsPDR15) and MAs efflux transporter (OsTOM1).

Zn-regulated transporters (ZIP family genes) are involved in Zn uptake from the soil in rice [182,183]. After absorption from the soil, Fe and Zn are transported via the xylem and phloem to plant organs. However, rice OsZIP5 and OsZIP8 orthologous genes have been identified in wheat that uptake Zn from the soil. Fe and Zn are transported into phloem mainly in the form of Fe (ll)- NA and Fe (ll)- DMA chelates and OsZIP4 is involved in loading of Zn into the phloem. Zn transport from phloem to xylem in rice is regulated by the YSL gene family, which has orthologs in wheat. OsYSL-2 is responsible for translocation of iron II-NA chelates through the phloem, OsYSL18, and OsYSL16 in Iron II-DMA chelate translocation, and OsYSL9 is involved in both kinds of metal chelate. Likely, the Zn-transporters ATPase, HMA, and OsHMA2 as homologs are involved in Zn translocation from xylem to phloem in rice and wheat [179,184].

Fe is stored primarily in small vacuoles, the aleurone, the subaleurone layer, and the seed coat in cereals. In rice, the vacuolar Fe transporter (VIT) family is involved mainly in iron storage. Two homologous VIT family genes, OsVIT1 and OsVIT2 of rice, also have orthologs in wheat. They function in Fe transportation [179]. Several other vacuolar Fe transporters: NRAMP1, NRAMP2, NRAMP5, NRAMP6, and NRAMP7 for Fe transport have orthologs in both rice and wheat [179,185]. Transgenic lines overexpressing ferritin genes in both rice and wheat accumulate 2–3 times more Fe in the seed endosperm and also have homology [186,187]. OsZIP6, OsMTP1, OsHRZ1, and OsHRZ2 are candidate genes for the transport of Fe and Zn in rice, repressing effects for Fe deficiency tolerance and protection from Fe toxicity have strong homology with wheat (Table 2). These rice genes involved in Fe and Zn uptake, transport or translocation, and accumulation can be further cloned and characterized for their orthologous genes in wheat.

7. Plant architecture

Plant architecture is the sum of all the phenological characters of a plant above the ground, including shoot branching and tillering, leaf primordial, axillary buds, plant height, and morphology of inflorescence. The characterization and isolation of genes involved in plant architecture of cereal crops have undergone extensive research. Yet, compared to wheat, rice has made far more progress in the genetic analysis for most of the plant type traits [95,194,195], especially inflorescence development and morphology [195]. This may be because wheat has multiple genomes, but with similar and repetitive structure. The genes and signaling systems that control rice inflorescence development may also be applicable to controlling wheat spike development and design [195]. Because tillering influences plant architecture and yield, much research has focused on tillering and plant height in both wheat and rice.

The SQUAMOSA-promoter binding protein-like (SPL) genes are transcriptional elements affecting plant architecture. Although they encode a small family of plant-specific transcription factors; they have diverse roles in plant growth and development. They show high potential for directly influencing plant architecture [196–198] as well as indirectly by modulating shoot architecture [199,200] and axillary bud formation [201,202]. There are several SPL wheat orthologs of rice, namely OsSPL3/5/10 [95]/14 [194] regulating plant architecture.

As compared to their rice orthologs, some TaSPLs showed divergent spatiotemporal expression patterns, suggesting functional difference [95]. TaSPLs may offer a novel genetic resource for influencing growth, development, and yield in cereal crops [95]. Owing to a lack of evidence for its molecular and physiological roles, the consequences of the OsSPL14 ortholog TaSPL14 on wheat plant architecture and yield are, however, still largely unclear [194]. In regulating plant height, panicle length, spikelet number, and thousand-grain weight, TaSPL14 and OsSPL14 function similarly, but they act differently during tiller development [194]. The OsSPL14 gene regulates optimum rice plant architecture, including tiller growth, panicle architecture, and stem lodging resistance, and as a result, increases grain yield [198,203]. OsSPL14 is a positive regulator of DEP1, a crucial element in the regulation of panicle architecture [198,204]. TaSPL14 may control spike development ia pathways involving genes (TaEIL1, TaERF1, and TaRAP2.11) other than DEP1. This suggests that TaSPL14 controls the ethylene-response pathway in order to control spike formation. Unlike OsSPL14 in rice, TaSPL14 has no effect on wheat tillering [194].

Tillering is an agronomic trait of both wheat and rice, and is also a determinant of plant type and yield. Strigolactones (SLs) inhibit the growth of plant collaterals and coordinate with auxin and cytokinin to regulate the formation of plant collaterals to maintain plant shape [205]. D53 nucleoprotein regulates plant tillering (shoots) as a "switch" of the SL signaling pathway. It provides an essential theoretical basis for plant-type improvement, especially of crops, and also provides help for breeders to solve the technical problem of using hybrid vigor. D53 is a SL-insensitive mutant. Fine mapping and map-based cloning revealed the DWARF 53 (D53) gene located at the end of the short arm of rice chromosome 11. It encodes a nuclear protein, D53, which is structurally similar to class I Clp ATPase [206]. In wheat, TaD27-B regulates tiller number via SL synthesis [207]. MiR156-TaSPLs interact with the SL signaling repressor TaD53 to regulate wheat tillering [199]. These studies confirm that SL controls wheat tillering. SL and auxins may regulate shoot branching. TaD27-RNAi plants show that SL affects wheat auxin signal transduction and biosynthesis [207]. Brassinosteroids (BRs) regulate tiller number. BRs and SL antagonistically regulated rice tillering through FC1 (TB1) under D53-OsBZR1 control [208]. TaD53 physically interacts with TaSPL3 to prevent it from upregulating wheat TaTB1 [199]. TaD53 may interact with BZR1 to inhibit FC1 expression, suggesting that BRs and SL in wheat have a similar function.

The genes encoding the GA response cascade have been identified using dwarf mutants of wheat and rice. A soluble GA receptor was identified as the basis of the rice GA-insensitive dwarf1 (GID1) mutant [209]. The development of dwarf and semi-dwarf rice cultivars has dramatically increased lodging resistance and yield potential since the 1950s. The GA receptor GID1 is essential to the GA signaling cascade. Homology cloning was used to identify three orthologous TaGID1 genes in wheat [210]. TaGID2s were closely related to OsGID2 in a GID2 protein phylogenetic analysis, suggesting that they have comparable roles in wheat [211]. Homologous cloning has revealed wheat tiller formation genes. TaMOC1, a GRAS transcription factor, may regulate axillary meristem initiation like rice MOC1. TaTB1 coordinates axillary spikelet formation during the vegetative-to-floral transition. Wheat and rice share gene functions, but developmental and phenotypic effects may differ. Axillary buds express MOC1 in rice, not the shoot apical meristem (SAM). OsTB1 inhibits lateral tillering and is absent in moc1 mutants. MOC1 activates MOC3 to upregulate FLORAL ORGAN NUMBER1 (FON1). TaMOC1 is expressed in leaf primordia epidermal cells, axillary buds, SAM, and young leaves. TaMOC1 develops spikelets. However, rice panicles and wheat spikes show that MOC1 and its wheat counterpart have different functions [64,212]. Wheat genes and their rice orthologs influencing plant architecture are listed in Table 1 and a list of rice genes influencing plant architecture, proposed as templates for cloning and characterization of their wheat orthologs, is presented in Table 2.

8. Concluding remarks and future perspectives

Comparative genomics studies between rice and wheat can play an important role in identifying conserved and unique genomic features, accelerating native trait discovery and deployment, and enhancing crop genetic and physiological potential through breeding and other crop improvement tools and practices. By deciphering insights from the simpler rice genome, researchers can expedite the identification of genes in the complex wheat genome for various traits of interest. Traditional methods might not effectively identify specific functional genes when assessing and selecting wheat genotypes based on their phenotypic assessments, which are often subject to being confounded by genotype by environment interaction of various magnitude. Integrating rice-wheat comparative genomics with Genome-Wide Association Studies and Quantitative Trait Loci mapping could speed up the identification and application of genes in wheat improvement. The comprehensive study by Bennetzen et al. [23] highlights the pivotal role that three decades of grass genome research have played in unraveling the mechanisms underpinning the evolution and structure of flowering plant genomes. Leveraging comparative genomics between rice and wheat, alongside cutting-edge techniques like whole-genome sequencing and genome editing for exploring gene functions, holds promise for accelerating wheat improvement and contributing to global food security efforts.

CRediT authorship contribution statement

Akila Wijerathna-Yapa: Conceptualization, Project administration, Writing – original draf, Writing – review & editing. Ruchi Bishnoi: Project administration, Writing – original draf, Writing – review & editing. Buddhini Ranawaka: Data curation, Formal analysis. Manu Maya Magar: Writing – original draf, Writing – review & editing. Hafeez Ur Rehman: Writing – original draf, Writing – review & editing. Swati G. Bharad: Writing – original draf. Michal T. Lorenc: Data curation, Formal analysis. Vinita Ramtekey: Writing – original draf. Sasha Gohar: Writing – original draf. Charu Lata: Writing – original draf. Md. Harun-Or-Rashid: Writing – original draf. Maryam Razzaq: Writing – original draf. Muhammad Sajjad: Conceptualization, Writing – original draf. Bhoja R. Basnet: Conceptualization, Writing – original draf, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors thank the International Maize and Wheat Improvement Center (CIMMYT) and Akila Wijerathna-Yapa and Buddhini Ranawaka for the Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture.

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ARTICLE INFO

Article history:

Received 27 June 2023

Revised 29 August 2023

Accepted 20 October 2023

Available online 11 November 2023

Footnote

* Corresponding authors.

E-mail addresses: [email protected] (A. Wijerathna-Yapa), [email protected] (B.R. Basnet).

1 These authors contributed equally to this work.

References

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